Abstract
Taxi trajectories reflect human mobility over the urban roads’ network. Although taxi drivers cruise the same city streets, there is an observed variation in their daily profit. To reveal the reasons behind this issue, this study introduces a novel approach for investigating and understanding the impact of human mobility patterns (taxi drivers’ behavior) on daily drivers’ profit. Firstly, a K-means clustering method is adopted to group taxi drivers into three profitability groups according to their driving duration, driving distance and income. Secondly, the cruising trips and stopping spots for each profitability group are extracted. Thirdly, a comparison among the profitability groups in terms of spatial and temporal patterns on cruising trips and stopping spots is carried out. The comparison applied various methods including the mash map matching method and DBSCAN clustering method. Finally, an overall analysis of the results is discussed in detail. The results show that there is a significant relationship between human mobility patterns and taxi drivers’ profitability. High profitability drivers based on their experience earn more compared to other driver groups, as they know which places are more active to cruise and to stop and at what times. This study provides suggestions and insights for taxi companies and taxi drivers in order to increase their daily income and to enhance the efficiency of the taxi industry.
Highlights
Taxis play a significant role in the travels of residents, tourists and other road users in the urban transportation system
There is an observed variation of the overall temporal patterns of taxi drivers during their cruising trips and stopping spots
We discuss the effects of the two parameters, without providing figures due to the page limitations, as follows: Firstly, we describe the effect of parameter MinPts by using the data of high profitability drivers in the period of 22:00–6:00 in September and October 2013; we can get the result of 70 clusters (Eps = 10, MinPt = 15) and 40 clusters (Eps = 10, MinPts = 5)
Summary
Taxis play a significant role in the travels of residents, tourists and other road users in the urban transportation system. A significant number of people are traveling by taxis in their daily movements around the world. According to a report issued in 2013 [1], taxi passengers’ traffic in 2012 recorded. 387 million passengers; the daily passenger travel mileage increased by 2.4%. Taxi idle rate decreased, and the empty-loading ratio was 29.6%. These numbers imply the yearly increment of occupancy frequency of taxi service in Wuhan City. Taxi drivers cruise the same streets, there is an observed variation in their incomes
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